Abstract In this paper, a fault tolerant model predictive control scheme is proposed for wind turbines in the partial-load region to meet the control objectives in the presence of disturbances, uncertainties, sensor and actuator faults. The aim of wind turbine control systems in the partial-load region is to capture maximum power by tracking the optimal generator speed. But any fault in the sensors and actuators can take away the closed-loop system from the main objectives and maybe make the system unstable in some cases. At first, an online model predictive controller (MPC) is designed as a nominal controller to track the maximum power and guarantee all constraints satisfaction without considering any fault. In the next step, an adaptive sliding mode observer (SMO) is designed to estimate the actual states and sensor faults, simultaneously. Finally, an additive control law is represented and shown that it is able to tolerate the actuator faults effectively. Using extensive simulation results it is shown that the proposed strategy is able to handle the uncertainties, sensor and actuator faults in the control system, simultaneously.

中文翻译：

---

使用模型预测容错控制的风力涡轮机可靠功率提取

摘要 在本文中，提出了一种容错模型预测控制方案，用于部分负荷区域的风力发电机组，以满足在存在扰动、不确定性、传感器和执行器故障的情况下的控制目标。部分负载区域中风力涡轮机控制系统的目标是通过跟踪最佳发电机速度来获取最大功率。但是传感器和执行器中的任何故障都会使闭环系统脱离主要目标，并在某些情况下可能使系统不稳定。首先，在线模型预测控制器 (MPC) 被设计为标称控制器，以跟踪最大功率并保证所有约束满足而不考虑任何故障。在下一步中，自适应滑模观测器 (SMO) 旨在同时估计实际状态和传感器故障。最后，表示并显示了一种附加控制律，它能够有效地容忍执行器故障。大量的仿真结果表明，所提出的策略能够同时处理控制系统中的不确定性、传感器和执行器故障。